Battery power limits estimation based on RC model

ABSTRACT

A method of estimating a maximum power limit of a battery cell at a specified prediction time using an improved RC equivalent circuit battery model and based on the battery cell&#39;s state of charge (SOC), temperature, and state of health (SOH). The method includes determining the battery cell&#39;s peak and continuous current limits, predicting a peak voltage after the specified prediction time based on the peak current limit, determining buffer values for the predicted peak voltage and the temperature of various battery components, setting a maximum current limit based on the buffer values, predicting a maximum voltage after the specified prediction time based on the maximum current limit, and determining a maximum power limit based on the predicted maximum voltage and the maximum current limit.

BACKGROUND

The present disclosure relates to a battery power limit estimationmethod, wherein the method is based on an RC equivalent circuit modelfor a battery cell.

Li-ion batteries are used as the source of energy for many electricalsystems, especially in hybrid electric vehicles (HEVs) and electricvehicles (EVs). In these vehicles, the battery interacts with othercomponents by means of a Battery Management System (BMS) to providepower to the vehicle and meet the vehicle's energy demand whilemaintaining the safety of the electrical system.

The reliability of these electrical systems is highly dependent of thehealth and safety of the battery, and therefore on the ability of theBMS to provide operation data that allows for peak performance withoutjeopardizing the health and safety of the battery. Controlling andmonitoring a battery installed in an HEV or EV is impossible without afast and accurate model of the battery to be used by the BMS. Li-ionbattery models have been used for estimating metrics of the battery,including state-of-charge (SOC), state-of-health (SOH), state-of-energy(SOE) and state-of-power (SOP). Also, the battery models are employed tohelp BMSs with the functions of battery control, real-time observation,parameter estimation, and optimization of the battery.

In all HEVs and EVs, it is necessary for the BMS to report the real-timepower capability of the battery pack to other vehicle systems such asthe Hybrid Control Unit (HCU). The SOP is used by the BMS to estimatethe power capability based on the battery current, SOC, temperature, andSOH. An accurate measure of this power capability is helpful inproviding the required power for the HEV or EV based on the driver'sdemand or different environmental conditions while ensuring that othersystems do not overtax the battery and jeopardize its health and safety.

In order to accurately estimate the battery power capability at apresent time, the cell voltage and temperature after a specifiedprediction time should be predicted and considered. Also, thetemperatures of other battery modules and pack components should beconsidered to protect these components and systems from reaching acritical working temperature due to power overdraw or overcharge.Therefore, it is necessary to have a model to calculate thesevariables—especially under different SOC, cell temperature, and SOHconditions. However, all presently available BMSs use a simple structurethat ignores these variables while determining power capability. Thishas caused inaccurate power calculation especially in aged batteries,batteries operating in low temperature conditions, and batteries withlow SOC. Inaccurate power estimates can result in systemunderperformance or operation outside of safe parameters.

Conventional methods for calculating battery power capability includethe Partnership for a New Generation of Vehicles (PNGV) Hybrid PulsePower Characterization (HPPC) method. This method uses an internalresistance look-up table for different SOC and temperature values topredict the battery cell voltage after a specified prediction time.However, this method does not take into consideration the effects of thebattery polarization level on power calculations. Therefore, theconventional method is not accurate in many cases, especially in casesof low SOC and temperature. To solve this problem, an interactive methodof estimation based on an improved battery model is needed to calculatethe battery polarization and consider it in the voltage and peak powerprediction process.

SUMMARY

Disclosed herein is a method of predicting a maximum power that abattery pack is able to provide or receive at a given time byconsidering all battery limits, including but not limited to minimumcell voltage, minimum battery voltage, maximum cell temperature, maximummodule temperature, and maximum pack components temperature. In oneembodiment, the method employs a RC model for a battery cell to predictthe voltage for the battery cell at a specified time in different SOC,temperature, current, voltage, and SOH conditions. In one embodiment,the method uses a buffer function to consider all the above listedbattery limitations for peak power calculation. In one embodiment, themethod may be used by vehicles such as (but not limited to) electricvehicles, hybrid electric vehicles, and plug-in hybrid electricalvehicles to calculate the peak current and/or the peak power of abattery pack installed in the vehicle.

Further disclosed herein is a system for estimating a maximum powerlimit of a battery cell at a specified prediction time, comprising asensor and a controller. In one embodiment, the sensor system isconfigured to receive a plurality of temperature measurements from aplurality of temperature sensors. In one embodiment, the controller isconfigured to receive data for a plurality of battery cell parametersand the plurality of temperature measurements from the sensor system. Inone embodiment, the controller is configured to estimate the maximumpower limit of the battery cell using a method such as the methoddisclosed above.

In one embodiment, the method of estimating a maximum power limit of abattery cell comprises determining a plurality of battery cellparameters; determining a peak current limit and a continuous currentlimit based on at least one of the plurality battery cell parameters;determining a predicted peak voltage using an RC equivalent circuitmodel of the battery cell, wherein at least one of a plurality RCequivalent circuit model parameters is set based on a specifiedprediction time, at least one of the plurality of battery cellparameters, and the peak current limit; determining a voltage buffervalue based on the predicted peak voltage; determining a temperaturebuffer value based on a plurality of temperature measurements;determining a maximum current limit based on a weight function appliedto the peak current limit and the continuous current limit, wherein theweight function value is determined based on the voltage buffer valueand the temperature buffer value; determining a predicted maximumvoltage based on the RC equivalent circuit model of the battery, whereinat least one of the plurality of RC equivalent circuit model parametersis set based on a specified prediction time, at least one of theplurality of battery cell parameters, and the peak current limit;determining a voltage buffer value based on the predicted peak voltage;and determining the maximum power limit based on the maximum currentlimit and the maximum voltage limit. In one embodiment, at least one ofthe plurality of parameters of the RC equivalent circuit model is setbased on the specified prediction time, at least one of the plurality ofbattery cell parameters, and the maximum current limit.

In one embodiment, the plurality of battery cell parameters includes atleast one of a state of charge (SOC) of the battery cell, a temperatureof the battery cell, and a state of health (SOH) of the battery cell.

In another disclosed embodiment, the maximum power limit is a maximumdischarge power limit, the peak current limit is a peak dischargecurrent limit, and the continuous current limit is a continuousdischarge current limit. In another disclosed embodiment, the maximumpower limit is a maximum charge power limit, the peak current limit is apeak charge current limit, and the continuous current limit is acontinuous charge current limit.

In another disclosed embodiment, the battery cell is a battery cellincluded in a battery module comprising at least one battery cell. Inanother disclosed embodiment, the battery module is a battery moduleincluded in a battery pack comprising at least one battery module.

In another disclosed embodiment, the plurality of temperaturemeasurements includes at least one measurement from the set of a maximumbattery cell temperature, a maximum battery module temperature, and amaximum battery pack components temperature. In another disclosedembodiment, the plurality of temperature measurements includes atemperature of at least one device related to the battery cell byproximity or by an electric connection to the battery cell.

In another disclosed embodiment, the RC equivalent circuit modelperforms a state of charge (SOC) calculation to predict what the stateof charge (SOC) will be after the specified prediction time has elapsedas part of determining the predicted peak voltage and the predictedmaximum voltage. In another disclosed embodiment, the RC equivalentcircuit model performs a state of charge (SOC) calculation to estimatethe state of charge (SOC) at an earlier time as part of determining thepredicted peak voltage and the predicted maximum voltage.

Other aspects, features, and techniques will be apparent to one skilledin the relevant art in view of the following detailed description of theembodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

The features, objects, and advantages of the disclosed embodiments willbecome more apparent from the detailed description set forth below whentaken in conjunction with the drawings in which like referencecharacters identify correspondingly throughout and wherein:

FIG. 1 is a perspective view of an exemplary embodiment of a vehicleincluding a battery pack with use for a power limit estimation method.

FIG. 2 is a flow diagram of an exemplary embodiment of a system forimplementing a power limit estimation method.

FIG. 3 is a block diagram of an exemplary embodiment of a power limitestimation method.

FIG. 4 is a circuit diagram of an exemplary embodiment of a two branchesRC model equivalent circuit for a battery cell.

FIG. 5 is a graphic illustration of an exemplary embodiment of arelationship between a discharge voltage buffer function and a predictedvoltage.

FIG. 6 is a graphic illustration of an exemplary embodiment of arelationship between a charge voltage buffer function and a predictedvoltage.

FIG. 7 is a graphic illustration of an exemplary embodiment of arelationship between a temperature buffer function and a temperature ofa battery component.

DETAILED DESCRIPTION

One aspect of the disclosure is directed to a power limit estimationmethod.

References throughout this document to “one embodiment,” “certainembodiments,” “an embodiment,” or similar term mean that a particularfeature, structure, or characteristic described in connection with theembodiment is included in at least one embodiment. Thus, the appearancesof such phrases in various places throughout this specification are notnecessarily all referring to the same embodiment. Furthermore, theparticular features, structures, or characteristics may be combined inany suitable manner on one or more embodiments without limitation. Forexample, two or more of the innovative methods described herein may becombined in a single method, but the application is not limited to thespecific exemplary combinations of methods that are described herein.

As used herein, the terms “a” or “an” shall mean one or more than one.The term “plurality” shall mean two or more than two. The term “another”is defined as a second or more. The terms “including” and/or “having”are open ended (e.g., comprising). The term “or” as used herein is to beinterpreted as inclusive or meaning any one or any combination.Therefore, “A, B or C” means “any of the following: A; B; C; A and B; Aand C; B and C; A, B and C”. An exception to this definition will occuronly when a combination of elements, functions, steps or acts are insome way inherently mutually exclusive.

The character “N” refers hereinafter to the last member of a set or thetotal count of members in a set. The character “X” refers hereinafter toa variable member of a set. The characters “A”, “B”, “C”, etc. refer toa specific but otherwise undefined member of a set.

A detailed description of various embodiments is provided; however, itis to be understood that the disclosed embodiments are merely exemplaryand may be embodied in various and alternative forms. The figures arenot necessarily to scale; some features may be exaggerated or minimizedto show details of particular components. Therefore, specific structuraland functional details disclosed herein are not to be interpreted aslimiting, but merely as a representative basis for teaching one skilledin the art to variously employ the disclosed embodiments.

FIG. 1 is a perspective view of an exemplary embodiment of a vehicle 100including a battery pack 210 with use for a power limit estimationmethod 300, wherein the power limit is a function of the continuouspower the battery pack 210 can deliver at a given time and the peakpower the battery pack 210 can deliver at a given time. The vehicle 100shown in FIG. 1 is exemplary. The power limit estimation method 300 maybe used with any vehicle including a battery pack or any other systemwith use for a battery power limit estimation method.

FIG. 2 is a flow diagram of an exemplary embodiment of a system 200 forimplementing a power limit estimation method 300. In one embodiment, thesystem 200 includes a battery pack 210, a controller 220, a sensorsystem 230, and a vehicle system 240, wherein the vehicle system 240 isconnected to the battery pack 210 by means of a power conduit 245. Inone embodiment, the system 200 receives data from other estimationsystems such as a state of charge (SOC) estimation system 250 and astate of health (SOH) estimation system 260.

In one embodiment, the battery pack 210 comprises at least one batterymodule 212, and each of the at least one battery modules 212 may furthercomprise at least one battery cell 215. In one embodiment, the powerlimit estimation method 300 is applied on a per-cell basis—the powerlimit estimation method 300 provides a power limit estimate for eachindividual battery cell 215. In another embodiment, the power limitestimation method 300 is applied on a per-module basis. In anotherembodiment, the power limit estimation method 300 is applied to thebattery pack 210 as a whole.

In one embodiment, the sensor system 230 comprises a plurality ofsensors, including but not limited to a cell temperature sensor 235 foreach battery cell 215 in the battery pack 210, a module temperaturesensor 232 for each battery module 212 in the battery pack 210, and amiscellaneous temperature sensor 231 for any miscellaneous components211 in the battery pack 210. In one embodiment, the sensor system 230passes sensor data from the plurality of sensors to the controller 220,whereafter the controller 220 determines a battery power limitestimation based at least in part on the sensor data. In one embodiment,the controller 220 may further base the determination of a battery powerlimit estimation based on a plurality of parameters provided by otherestimation systems such as a state of charge (SOC) estimation system 250and a state of health (SOH) estimation system 260.

In another embodiment, the battery pack 210 discharges power to thevehicle system 240 across the power conduit 245. In one embodiment,after the controller 220 determines a power limit estimation, thecontroller 220 sends instructions to the battery pack 210 not to providemore power to the vehicle system 240 than is allowable under the powerlimit. In another embodiment, after the controller 220 determines apower limit estimation, the controller 220 sends instructions to thevehicle system 240 not to draw more power from the battery pack 210 thanis allowable under the power limit.

In another embodiment, the battery pack 210 charges power using thevehicle system 240 across the power conduit 245. In this embodiment, thevehicle system 240 may be a dedicated charging system such as a solarpanel grid or an alternating charging system, such as a motor inregenerative breaking mode. In one embodiment, after the controller 220determines a power limit estimation, the controller 220 sendsinstructions to the battery pack 210 not to charge more power from thevehicle system 240 than is allowable under the power limit. In anotherembodiment, after the controller 220 determines a power limitestimation, the controller 220 sends instructions to the vehicle system240 not to provide more power to the battery pack 210 than is allowableunder the power limit.

FIG. 3 is a block diagram of an exemplary embodiment of a power limitestimation method 300, wherein the power limit estimation method 300 isapplied to a battery cell 215. In one embodiment, the power limitestimation method 300 comprises a continuous current limit block 310, apeak current limit block 320, a capacity block 330, a peak voltageprediction block 340, a discharge/charge voltage buffer function block350, a temperature buffer function block 360, a discharge/charge currentcapability block 370, a max voltage prediction block 380, and a powercapability calculation block 390. In one embodiment, the power limitestimation method 300 estimates a power limit based on a plurality ofbattery cell parameters. In one embodiment, the parameters of theplurality of battery cell parameters include the state of charge (SOC)of the battery cell 215, the temperature T_(cell) of the battery cell215, and the state of health (SOH) of the battery cell 215.

In one embodiment, the continuous current limit block 310 determines acontinuous discharge current limit I_(dischg,cont) and a continuouscharge current limit I_(chg,cont) based on the state of charge (SOC) ofthe battery cell 215, the temperature T_(cell) of the battery cell 215,and the state of health (SOH) of the battery cell 215. In oneembodiment, I_(dischg,cont) and I_(chg,cont) act as a safe operationlimit for the battery cell 215—as long as the charge and dischargecurrent to and from the battery cell 215 remain at a magnitude lowerthan I_(dischg,cont) and I_(chg,cont), the battery cell 215 will operatesafely.

In one embodiment, the peak current limit block 320 determines a peakdischarge current limit I_(dischg,peak) and a peak charge current limitI_(chg,peak) based on the state of charge (SOC) of the battery cell 215,the temperature T_(cell) of the battery cell 215, and the state ofhealth (SOH) of the battery cell 215. As with battery continuous currentlimits, all Li-ion cell manufacturers report the discharge peak currentlimits (I_(dischg,peak)) and the charge peak limits (I_(chg,peak)) ofthe battery cell 215 in different SOC and temperature conditions for 10second pulses of discharge or charge duration. In one embodiment, thereported peak current limits are the current capability of the batterycell 215 for different SOC and temperature values, assuming that thebattery cell 215 is discharged or charged from rest and open circuitvoltage (i.e. the battery is not carrying a load). However, themanufacturer-reported peak current limits do not factor in alternatestarting conditions, such as the possibility that a battery cell mightbe expected to discharge shortly after a charge cycle. Further, thereported peak current limits do not factor in design limitations at thebattery module 212 or battery pack 210 level. In one embodiment, it ispossible to correct these oversights by use of an improved currentlimit; an improved current limit estimation method may be used by thecontinuous current limit block 310 and/or the peak current limit block320.

In one embodiment, the capacity block 330 determines the capacity of thebattery cell 215 based on the state of health (SOH) of the battery cell215. In one embodiment, the capacity is defined as the usable chargecapacity of the battery cell 215 at 25° C. with 1C constant dischargerate and a given SOH value, with usable charge capacity measured from afull charge to a minimum charge defined by a cut-off voltage.

In one embodiment, the peak voltage prediction block 340 predicts thecell voltage based on the discharge and charge peak current limits. Inone embodiment, the predicted peak cell voltage is considered in thedischarge/charge voltage buffer function 350. In one embodiment, thepeak voltage prediction block 340 consists of two parts: SOC Calculationand Voltage prediction.

In order to predict the cell voltage at prediction time t_(K) secondsfrom the present time, it is necessary to estimate the final SOCresulting from applying I_(dischg,peak) or I_(chg,peak) to discharge orcharge the battery over the course of t_(K) seconds. In one embodiment,SOC_(dischg,final) is defined as the SOC value for the battery cell 215after the cell is discharged at a rate of I_(dischg,peak) for aspecified prediction time t_(K) and SOC_(chg,final) is defined as theSOC value for the battery cell 215 after the cell is charged at a rateof I_(chg,peak) for a specified prediction time t_(K). In oneembodiment, the prediction of the final SOC is calculated as follows:

${SOC}_{{dischg},{final}} = {{SOC}_{0} + \frac{I_{{dischg} \cdot {peak}} \times t_{K}}{Capacity}}$${SOC}_{{chg},{final}} = {{SOC}_{0} + \frac{I_{{chg} \cdot {peak}} \times t_{K}}{Capacity}}$wherein SOC₀ is the SOC value for the battery cell 215 at the presenttime and t_(K) is the specified prediction time for which the powerlimit estimation method 300 is reporting the power capability. In oneembodiment, t_(K) can vary depending on which control strategies the HCUis using. In one embodiment, if SOC_(dischg,final) is less thanSOC_(min) (e.g. the battery cell 215 is expected to fully dischargeduring the prediction time t_(K)), the final SOC value will be set atthe SOC_(min) and I_(dischg,peak) will be recalculated as follows:

$I_{{dischg} \cdot {peak}} = \frac{{SOC}_{\min} - {SOC}_{0}}{\left( {t_{K}/{Capacity}} \right)}$such that discharging at the reported discharge current limit will notdischarge more from the battery cell 215 than what is needed to maintaina minimum SOC. In one embodiment, if the SOC_(chg,final) is higher thanSOC_(max) (e.g. the battery cell 215 is expected to be fully chargedduring the prediction time t_(K)), then the final SOC value will be setat the SOC_(max) and I_(chg,peak) will be recalculated as follows:

$I_{{chg} \cdot {peak}} = \frac{{SOC}_{\max} - {SOC}_{0}}{\left( {t_{K}/{Capacity}} \right)}$such that charging at the reported charge current limit will not chargethe battery cell 215 more than what is allowable based on a maximum SOC.In one embodiment, SOC_(min) and SOC_(max) are set based on designparameters for operation of the battery cell 215.

In one embodiment, this SOC definition's value for capacity is updatedbased on the capacity determined by the capacity block 330. In oneembodiment, the SOH value is estimated by a SOH block in the BMS.

In one embodiment, to calculate the power capability, it is necessary tohave a battery model to predict the cell voltage after a sampling periodΔt if the battery is discharged or charged by I_(dischg,peak) orI_(chg,peak), respectively. This model can be imperial or aphysics-based model. In one embodiment, a two branches RC model 400 (seeFIG. 4) is used to predict the cell voltage and model the batterypolarization level in response to various conditions. FIG. 4 is acircuit diagram depicting an exemplary embodiment of a RC model 400 foruse in the power limit estimation method 300. In one embodiment, all RCparameters (including but not limited to R₀, C₁, R₁, C₂, R₂, and OCV)may be estimated by using a look-up table populated with data from testsperformed on the battery cell 215. In one embodiment, R₀ is determinedas a function of the state of charge (SOC) of the battery cell 215, thebattery cell 215 temperature T_(cell), and the state of health (SOH) ofthe battery cell 215. In one embodiment, OCV is determined as a functionof the state of charge (SOC) of the battery cell 215, the battery cell215 temperature T_(cell), and the state of health (SOH) of the batterycell 200. In one embodiment, C₁, R₁, C₂, and R₂ are determined as afunction of the state of charge (SOC) of the battery cell 215, theequivalent circuit current I, the battery cell 215 temperature T_(cell),and the state of health (SOH) of the battery cell 200. In oneembodiment, the parameters of the RC model 400 are predicted by means ofan unscented Kalman filter method.

In one embodiment, by using RC model 400, the cell terminal voltage(V_(t)) at time t_(k) can be calculated as follows:

V_(t, k) = OCV_(k) + I_(k) × R_(0, k) + U_(1, k − 1)e^(−Δ t/(R₁C₁)) + I_(k) × R_(1, k)(1 − e^(−Δ t/(R₁C₁))) + U_(2, k − 1)e^(−Δ t/(R₂C₂)) + I_(k) × R_(2, k)(1 − e^(−Δ t/(R₂C₂)))wherein Δt is the incremental sampling period of the batterymeasurement, k is the sampling step number, and K is the number ofsampling steps taken (such that 1≤k≤K and KΔt=t_(K)). In one embodiment,in order to predict the cell voltage, this equation is solved byassuming constant current discharge or charge at I_(dischg,peak) orI_(chg,peak) for the specified prediction time t_(K). The initial valuesof U₁ and U₂ are also necessary to solve the equation and should beestimated alongside the battery SOC at the SOC block. In one embodiment,the initial values of U₁ and U₂ are treated as 0. In one embodiment, ifthe predicted discharge voltage is less than V_(min), or the predictedcharge voltage is higher than V_(max), then the battery peak currentlimits may be revised based on those minimum and maximum cell voltagelimits.

In one embodiment, the discharge/charge buffer function block 350defines a discharge voltage buffer value or a charge voltage buffervalue based on the predicted cell voltage determined by the peak voltageprediction block 340, wherein the charge/discharge voltage buffer valueis a weight function representing a limit on the ability of the batterycell 215 to charge or discharge current. In one embodiment, thedischarge/charge buffer function block 350 determines a discharge buffervalue based on a cell peak discharge voltage value predicted by the peakvoltage prediction block 340. The discharge buffer function may bedetermined by a piecewise function such as the function represented inFIG. 5. In one embodiment, the discharge/charge buffer function block350 determines a charge buffer value based on a cell peak charge voltagevalue predicted by the peak voltage prediction block 340. The chargebuffer function may be determined by a piecewise function such as thefunction represented in FIG. 6.

In one embodiment, the temperature buffer function block 360 determinesa value for a temperature buffer function wherein the temperature bufferfunction is a weight function representing a limit on the ability of thebattery cell 215 to charge or discharge current. In one embodiment, thetemperature buffer function is defined based on the temperature of eachbattery component, and is represented as a piecewise function such asthe function represented in FIG. 7—the temperature buffer functiongradually drops in value from 1 to 0 between two temperature maximumlimits T_(max,1) and T_(max,2). Different batteries may have differenttemperature buffer functions; however, in the primary embodiment, it isnecessary to have three temperature buffer functions as follows:

Cell Temperature buffer function: The maximum temperature of all cellsin the battery pack 210 should be considered in determining the batterycurrent capability. The first T_(max) limit may be set at 40° C. and thesecond T_(max) limit may be set at 55° C.

Module Temperature buffer function: The maximum temperature of allmodules in the battery pack 210 should be considered in determining thebattery current capability. The first T_(max) limit may be set at 40° C.and the second T_(max) limit may be set at 70° C.

Pack Components Temperature buffer function: The maximum temperature ofat least one of the pack components in the battery pack 210 should beconsidered in determining the battery current capability. The firstT_(max) limit may be set at 40° C. and the second T_(max) limit may beset at 100° C.

In one embodiment, the battery discharge/charge current capability block370 determines a maximum discharge current value I_(dischg,max) and amaximum charge current value I_(chg,max) based on I_(dischg,peak),I_(chg,peak), I_(dischg,cont), I_(chg,cont), and the plurality of buffervalues determined by the charge/discharge voltage buffer function block350 and the temperature buffer function block 360.

In one embodiment, the battery maximum current capability can be definedas a value between the peak current limit and continuous current limitas follows:I _(dischg,max)=α_(dischg) ×I _(dischg,peak)+(1−α_(dischg))×I_(dischg,cont)I _(chg,max)=α_(chg) ×I _(chg,peak)+(1−α_(chg))×I _(chg,cont)where α is the buffer function, a weight function with a value betweenzero and one. In one embodiment, this function represents the capabilityof the battery to deliver discharge or charge peak currents. In oneembodiment, if the buffer value is 1, the battery is 100% capable ofdischarging at the peak discharge current value (or charging at the peakcharge current value), and 0% capable if the buffer value is 0. In oneembodiment, to quantify the buffer function, it is necessary to quantifythe battery limitations preventing the battery from using 100% peakcurrents.

In one embodiment, α_(dischg) and α_(chg) are determined as minimumvalues from the set of corresponding values determined by thedischarge/charge voltage buffer function block 350 and the temperaturebuffer function block 360, such that if any one buffer value produced byeither of the two blocks 350 and 360 indicates a condition that wouldrestrict or prevent the battery cell from delivering peak dischargepower or receiving peak charge power, α_(dischg) and α_(chg) are reducedand the battery discharge/charge current capability block 370 weighs thecontinuous current value more heavily in determining a present maximumdischarge/charge current value.

In one embodiment, the max voltage prediction block 380 predicts thecell voltage based on the discharge and charge maximum current limitsdetermined by the battery discharge/charge current capability block 370.The max voltage prediction block 380 may use the same function and RCmodel 400 as the peak voltage prediction block 340, except withI_(dischg,max) and I_(chg,max) as the inputs instead of I_(dischg,peak)and I_(chg,peak).

In one embodiment, the power capability calculation block 390 determinesa maximum discharge and charge power based on I_(dischg,max),I_(chg,max), and the cell voltage predicted at the max voltageprediction block 380. In one embodiment, the maximum discharge andcharge power may be determined as follows:P _(dischg,max) =I _(dischg,max) ×V _(dischg,predict)P _(chg,max) =I _(chg,max) ×V _(chg,predict)

While this disclosure makes reference to exemplary embodiments, it willbe understood by those skilled in the art that various changes in formand details may be made therein without departing from the scope of theclaimed embodiments.

What is claimed is:
 1. A method of estimating a maximum power limit of abattery cell at a specified prediction time, comprising: determining aplurality of battery cell parameters; determining a peak current limitand a continuous current limit based on at least one of the plurality ofbattery cell parameters; determining a predicted peak voltage using anRC equivalent circuit model of the battery cell, wherein at least one ofa plurality of RC equivalent circuit model parameters is set based onthe specified prediction time, at least one of the plurality of batterycell parameters, and the peak current limit; determining a voltagebuffer value based on the predicted peak voltage; determining atemperature buffer value based on a plurality of temperaturemeasurements; determining a maximum current limit based on a weightfunction applied to the peak current limit and the continuous currentlimit, wherein the weight function value is determined based on thevoltage buffer value and the temperature buffer value; determining apredicted maximum voltage based on the RC equivalent circuit model ofthe battery, wherein at least one of the plurality of RC equivalentcircuit model parameters is set based on the specified prediction time,at least one of the plurality of battery cell parameters, and themaximum current limit; and determining the maximum power limit based onthe maximum current limit and the maximum voltage limit.
 2. The methodof claim 1, wherein the plurality of battery cell parameters includes atleast one of a state of charge (SOC) of the battery cell, a temperatureof the battery cell, and a state of health (SOH) of the battery cell. 3.The method of claim 1, wherein the maximum power limit is a maximumdischarge power limit, the peak current limit is a peak dischargecurrent limit, and the continuous current limit is a continuousdischarge current limit.
 4. The method of claim 1, wherein the maximumpower limit is a maximum charge power limit, the peak current limit is apeak charge current limit, and the continuous current limit is acontinuous charge current limit.
 5. The method of claim 1, wherein thebattery cell is a battery cell included in a battery module comprisingat least one battery cell.
 6. The method of claim 5, wherein the batterymodule is a battery module included in a battery pack comprising atleast one battery module.
 7. The method of claim 6, wherein theplurality of temperature measurements includes at least one measurementfrom the set of a maximum battery cell temperature, a maximum batterymodule temperature, and a maximum battery pack components temperature.8. The method of claim 1, wherein the plurality of temperaturemeasurements includes a temperature of at least one device related tothe battery cell by proximity or by an electric connection to thebattery cell.
 9. The method of claim 1, wherein the RC equivalentcircuit model performs a state of charge (SOC) calculation to determinea predicted state of charge (SOC) after the specified prediction timehas elapsed as part of determining the predicted peak voltage and thepredicted maximum voltage.
 10. The method of claim 1, wherein the RCequivalent circuit model performs a state of charge (SOC) calculation todetermine an estimated state of charge (SOC) at an earlier time as partof determining the predicted peak voltage and the predicted maximumvoltage.
 11. A system for estimating a maximum power limit of a batterycell at a specified prediction time, comprising: a sensor system,wherein the sensor system is configured to receive a plurality oftemperature measurements from a plurality of temperature sensors; and acontroller, wherein the controller is configured to receive data for aplurality of battery cell parameters and the plurality of temperaturemeasurements from the sensor system, and wherein the controller isconfigured to estimate the maximum power limit of the battery cell usinga method comprising: determining a peak current limit and a continuouscurrent limit based on at least one of the plurality of battery cellparameters; determining a predicted peak voltage using an RC equivalentcircuit model of the battery cell, wherein at least one of a pluralityof RC equivalent circuit model parameters is set based on the specifiedprediction time, at least one of the plurality of battery cellparameters, and the peak current limit; determining a voltage buffervalue based on the predicted peak voltage; determining a temperaturebuffer value based on the plurality of temperature measurements;determining a maximum current limit based on a weight function appliedto the peak current limit and the continuous current limit, wherein theweight function value is determined based on the voltage buffer valueand the temperature buffer value; determining a predicted maximumvoltage based on the RC equivalent circuit model of the battery, whereinat least one of the plurality of RC equivalent circuit model parametersis set based on the specified prediction time, at least one of theplurality of battery cell parameters, and the maximum current limit; anddetermining the maximum power limit based on the maximum current limitand the maximum voltage limit.
 12. The system of claim 11, wherein theplurality of battery cell parameters includes at least one of a state ofcharge (SOC) of the battery cell, a temperature of the battery cell, anda state of health (SOH) of the battery cell.
 13. The system of claim 11,wherein the maximum power limit is a maximum discharge power limit, thepeak current limit is a peak discharge current limit, and the continuouscurrent limit is a continuous discharge current limit.
 14. The system ofclaim 11, wherein the maximum power limit is a maximum charge powerlimit, the peak current limit is a peak charge current limit, and thecontinuous current limit is a continuous charge current limit.
 15. Thesystem of claim 11, wherein battery cell is a battery cell included in abattery module comprising at least one battery cell.
 16. The system ofclaim 15, wherein the battery module is a battery module included in abattery pack comprising at least one battery module.
 17. The system ofclaim 16, wherein the plurality of temperature measurements includes atleast one measurement from the set of a maximum battery celltemperature, a maximum battery module temperature, and a maximum batterypack components temperature.
 18. The system of claim 11, wherein theplurality of temperature measurements includes a temperature of at leastone device related to the battery cell by proximity or by an electricconnection to the battery cell.
 19. The system of claim 11, wherein theRC equivalent circuit model performs a state of charge (SOC) calculationto determine a predicted state of charge (SOC) after the specifiedprediction time has elapsed as part of determining the predicted peakvoltage and the predicted maximum voltage.
 20. The system of claim 11,wherein the RC equivalent circuit model performs a state of charge (SOC)calculation to determine an estimated state of charge (SOC) at anearlier time as part of determining the predicted peak voltage and thepredicted maximum voltage.